A Stabilizing Model Predictive Control for Nonlinear Fractional Order Systems with Polytopic Model

K. Arnavaz, S. Nikravesh
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Abstract

In this paper, a model predictive control (MPC) algorithm is proposed for a class of discrete-time nonlinear fractional order systems with input constraints. A polytopic linear model (PLM) is employed to approximate the nonlinear system. Moreover, a finite-dimensional approximation is utilized for the fractional order dynamics. To calculate the stabilizing state-feedback MPC law, a constrained min-max optimization problem is solved at each sampling instant over an infinite time horizon which guarantees the robust stability of the closed-loop system. The effectiveness of the proposed algorithm is validated by a simulation example.
具有多边形模型的非线性分数阶系统的稳定模型预测控制
针对一类具有输入约束的离散非线性分数阶系统,提出了一种模型预测控制算法。采用多面体线性模型(PLM)逼近非线性系统。此外,对分数阶动力学采用了有限维近似。为了计算稳定状态反馈MPC律,在无限时间范围内求解每个采样时刻的约束最小-最大优化问题,保证闭环系统的鲁棒稳定性。通过仿真算例验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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